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Sex differences are commonly observed in behaviors that are closely linked to adaptive function, but sex differences can also be observed in behavioral "building blocks" such as locomotor activity and reward processing. Modern neuroscientific inquiry, in pursuit of generalizable principles of functioning across sexes, has often ignored these more subtle sex differences in behavioral building blocks that may result from differences in these behavioral building blocks. A frequent assumption is that there is a default (often male) way to perform a behavior. This approach misses fundamental drivers of individual variability within and between sexes. Incomplete behavioral descriptions of both sexes can lead to an overreliance on reduced "single-variable" readouts of complex behaviors, the design of which may be based on male-biased samples. Here, we advocate that the incorporation of new machine-learning tools for collecting and analyzing multimodal "big behavior" data allows for a more holistic and richer approach to the quantification of behavior in both sexes. These new tools make behavioral description more robust and replicable across laboratories and species, and may open up new lines of neuroscientific inquiry by facilitating the discovery of novel behavioral states. Having more accurate measures of behavioral diversity in males and females could serve as a hypothesis generator for where and when we should look in the brain for meaningful neural differences.

Chronic stress can have lasting adverse consequences in some individuals, yet others are resilient to the same stressor(1,2). Susceptible and resilient individuals exhibit differences in the intrinsic properties of mesolimbic dopamine (DA) neurons after the stressful experience is over(3–8). However, the causal links between DA, behaviour during stress and individual differences in resilience are unknown. Here we recorded behaviour in mice simultaneously with DA neuron activity in projections to the nucleus accumbens (NAc) (which signals reward(9–12)) and the tail striatum (TS) (which signals threat(13–16)) during social defeat. Supervised and unsupervised behavioural quantification revealed that during stress, resilient and susceptible mice use different behavioural strategies and have distinct activity patterns in DA terminals in the NAc (but not the TS). Neurally, resilient mice have greater activity near the aggressor, including at the onset of fighting back. Conversely, susceptible mice have greater activity at the offset of attacks and onset of fleeing. We also performed optogenetic stimulation of NAc-projecting DA neurons in open loop (randomly timed) during defeat or timed to specific behaviours using real-time behavioural classification. Both open-loop and fighting-back-timed activation promoted resilience and reorganized behaviour during defeat towards resilience-associated patterns. Together, these data provide a link between DA neural activity, resilience and resilience-associated behaviour during the experience of stress.

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation in tools to quantify natural animal behavior. While advances in deep learning and computer vision have enabled markerless pose estimation in individual animals, extending these to multiple animals presents unique challenges for studies of social behaviors or animals in their natural environments. Here we present Social LEAP Estimates Animal Poses (SLEAP), a machine learning system for multi-animal pose tracking. This system enables versatile workflows for data labeling, model training and inference on previously unseen data. SLEAP features an accessible graphical user interface, a standardized data model, a reproducible configuration system, over 30 model architectures, two approaches to part grouping and two approaches to identity tracking. We applied SLEAP to seven datasets across flies, bees, mice and gerbils to systematically evaluate each approach and architecture, and we compare it with other existing approaches. SLEAP achieves greater accuracy and speeds of more than 800 frames per second, with latencies of less than 3.5 ms at full 1,024 × 1,024 image resolution. This makes SLEAP usable for real-time applications, which we demonstrate by controlling the behavior of one animal on the basis of the tracking and detection of social interactions with another animal.

Social behaviors, like other motivated behaviors, frequently consist of a flexible motivated-seeking or approach phase followed by social action. Dysregulated social behavior may arise from changes to motivation, wherein individuals fail to enter a motivated seeking state, or may be in the execution of the social action itself. However, it is unclear how the brain generates and gates this flexible motivation-to-action sequence, and whether aggressive motivation and action are controlled by separate circuit mechanisms. Here, we record populations of neurons in the ventromedial hypothalamus ventrolateral area (VMHvl) of male mice at cellular resolution during “free” aggression and also during an aggression operant task, where the behaviors that precede attack are stereotyped. We find that this population encodes the temporal sequence of aggressive motivation to action and that the temporal selectivity of neurons is invariant to differences in motivated behavior. To test whether motivation and action could be independently regulated, we focused on two key inhibitory inputs to the VMHvl: a source of local inhibition (VMHvl shell) and the primary source of long-range inhibition (the medial preoptic area, MPO). While we find that the VMHvl receives broad monosynaptic inhibitory input from both inputs, optogenetic perturbation of these inputs during recording reveals temporal selectivity during aggressive motivation and action, suggesting specificity of function. Encoding models applied to population calcium recordings of these inhibitory inputs during naturalistic social interactions and during the social operant task further reveal that these inputs have different temporal dynamics during aggression: VMHvl shellvgat+activity peaks at the start of aggressive interactions, while MPO-VMHvlvgat+activity peaks at behaviorally aligned endpoints of aggressive interactions. Finally, using closed-loop optogenetic stimulation timed to specific phases of the aggression-operant task, we find a double-dissociation of the effects on aggressive motivation and action: activation of MPO-VMHvlvgat+, even briefly and temporally distant from the initiation of aggression, produces long-lasting motivational deficits, delaying the initiation of aggression and generating behaviors consistent with an unmotivated state. In contrast, activation of VMHvl shellvgat+produces acute action-related deficits, causing an exit from an attack state. Fitting a Hidden Markov Model (HMM) to behavior further corroborates these findings by showing that MPO-VMHvlvgat+stimulation prolongs a low motivation state and VMHvl shellvgat+promotes exit from an attack state. Together, these data demonstrate how separable inhibitory circuits in the hypothalamus can independently gate the motivational and action phases of aggression through a single locus of control.

Anxiety is a negative emotional state that is overly displayed in anxiety disorders and depression. Although anxiety is known to be controlled by distributed brain networks, key components for its initiation, maintenance and coordination with behavioral state remain poorly understood. Here, we report that anxiogenic stressors elicit acute and prolonged responses in glutamatergic neurons of mouse medial preoptic area (mPOA). These neurons encode extremely negative valence, and mediate induction and expression of anxiety-like behaviors. Conversely, mPOA GABAergic neurons encode positive valence and produce anxiolytic effects. Such opposing roles are mediated by their competing local interactions and long-range projections to the periaqueductal gray. The two neuronal populations antagonistically regulate anxiety-like and parental behaviors: anxiety is reduced while parenting is enhanced and vice versa. Thus, by evaluating negative and positive valences through distinct but interacting circuits, mPOA coordinates emotional state and social behavior.

The desire to understand how the brain generates and patterns behavior has driven rapid methodological innovation to quantify and model natural animal behavior. This has led to important advances in deep learning-based markerless pose estimation that have been enabled in part by the success of deep learning for computer vision applications. Here we present SLEAP (Social LEAP Estimates Animal Poses), a framework for multi-animal pose tracking via deep learning. This system is capable of simultaneously tracking any number of animals during social interactions and across a variety of experimental conditions. SLEAP implements several complementary approaches for dealing with the problems inherent in moving from single-to multi-animal pose tracking, including configurable neural network architectures, inference techniques, and tracking algorithms, enabling easy specialization and tuning for particular experimental conditions or performance requirements. We report results on multiple datasets of socially interacting animals (flies, bees, and mice) and describe how dataset-specific properties can be leveraged to determine the best configuration of SLEAP models. Using a high accuracy model (sleap.ai.

Persistent negative emotional states, such as anxiety, suppress social behavior and vice versa. A new report identifies a novel neural circuit that generates persistent anxiety states and describes how competing excitatory and inhibitory components of this circuit battle to pattern social behavior.

SummaryWhile the ventromedial hypothalamus, ventrolateral area (VMHvl) is now well established as a critical locus for the generation of conspecific aggression, its role is complex, with populations of neurons responding during the motivational, sensory, and action phases of aggression, and also during social interactions with the opposite sex. It has been previously unclear how the brain uses this complex multidimensional signal and generates a discrete action: the attack. Here we find that the largest posterior target of the VMHvl, the lateral periaqueductal gray (lPAG) encodes a simplified attack-selective signal during aggression. Single units in the lPAG exhibit greater selectivity for the attack action during aggression than VMHvl neurons and a subpopulation of neurons in the PAG exhibit short-latency, time-locked spiking relative to the activity of jaw muscles for biting during attack. In addition, channelrhodopsin assisted circuit mapping reveals a preferential projection from VMHvl glutamatergic cells to lPAG glutamatergic cells. Using projection-specific fiber photometry, we find that this excitatory projection conveys male-biased signals from the VMHvl to downstream glutamatergic PAG neurons that integrate ongoing male-related activity over several seconds, which suggests that action-selectivity is generated by a combination of both pre and postsynaptic filtering mechanisms.

Although the ventromedial hypothalamus ventrolateral area (VMHvl) is now well established as a critical locus for the generation of conspecific aggression, its role is complex, with neurons responding during multiple phases of social interactions with both males and females. It has been previously unclear how the brain uses this complex multidimensional signal and coordinates a discrete action: the attack. Here, we find a hypothalamic-midbrain circuit that represents hierarchically organized social signals during aggression. Optogenetic-assisted circuit mapping reveals a preferential projection from VMHvlvGlut2 to lPAGvGlut2 cells, and inactivation of downstream lPAGvGlut2 populations results in aggression-specific deficits. lPAG neurons are selective for attack action and exhibit short-latency, time-locked spiking relative to the activity of jaw muscles during biting. Last, we find that this projection conveys male-biased signals from the VMHvl to downstream lPAGvGlut2 neurons that are sensitive to features of ongoing activity, suggesting that action selectivity is generated by a combination of pre- and postsynaptic mechanisms.

Tinbergen proposed that instinctive behaviors can be divided into appetitive and consummatory phases. During mating and aggression, the appetitive phase contains various actions to bring an animal to a social target and the consummatory phase allows stereotyped actions to take place. Here, we summarize recent advances in elucidating the neural circuits underlying the appetitive and consummatory phases of sexual and aggressive behaviors with a focus on male mice. We outline the role of the main olfactory inputs in the initiation of social approach; the engagement of the accessory olfactory system during social investigation, and the role of the hypothalamus and its downstream pathways in orchestrating social behaviors through a suite of motor actions.

In many vertebrate species, certain individuals will seek out opportunities for aggression, even in the absence of threat-provoking cues. Although several brain areas have been implicated in the generation of attack in response to social threat, little is known about the neural mechanisms that promote self-initiated or 'voluntary' aggression-seeking when no threat is present. To explore this directly, we utilized an aggression-seeking task in which male mice self-initiated aggression trials to gain brief and repeated access to a weaker male that they could attack. In males that exhibited rapid task learning, we found that the ventrolateral part of the ventromedial hypothalamus (VMHvl), an area with a known role in attack, was essential for aggression-seeking. Using both single-unit electrophysiology and population optical recording, we found that VMHvl neurons became active during aggression-seeking and that their activity tracked changes in task learning and extinction. Inactivation of the VMHvl reduced aggression-seeking behavior, whereas optogenetic stimulation of the VMHvl accelerated moment-to-moment aggression-seeking and intensified future attack. These data demonstrate that the VMHvl can mediate both acute attack and flexible seeking actions that precede attack.

Little is known about the internal circuitry of the primate lateral intraparietal area (LIP). During two versions of a delayed-saccade task, we found radically different network dynamics beneath similar population average firing patterns. When neurons are not influenced by stimuli outside their receptive fields (RFs), dynamics of the high-dimensional LIP network during slowly varying activity lie predominantly in one multi-neuronal dimension, as described previously. However, when activity is suppressed by stimuli outside the RF, slow LIP dynamics markedly deviate from a single dimension. The conflicting results can be reconciled if two LIP local networks, each underlying an RF location and dominated by a single multi-neuronal activity pattern, are suppressively coupled to each other. These results demonstrate the low dimensionality of slow LIP local dynamics, and suggest that LIP local networks encoding the attentional and movement priority of competing visual locations actively suppress one another.

The hypothalamus was first implicated in the classic fight or flight response nearly a century ago, and since then, many important strides have been made in understanding both the circuitry and the neural dynamics underlying the generation of these behaviors. In this review, we will focus specifically on the role of the hypothalamus in aggression, paying particular attention to recent advances in the field that have allowed for functional identification of relevant hypothalamic subnuclei. Recent progress in this field has been aided by the development of new techniques for functional manipulation including optogenetics and pharmacogenetics, as well as advances in technology used for chronic in vivo recordings during complex social behaviors. We will examine the role of the hypothalamus through the complimentary lenses of 1) loss of function studies, including pharmacology and pharmacogenetics, 2) gain of function studies, including specific comparisons between results from classic electrical stimulation studies and more recent work using optogenetics, and 3) neural activity, including both immediate early gene and awake-behaving recordings. Lastly, we will outline current approaches to identifying the precise role of the hypothalamus in promoting aggressive motivation and aggressive action.